Senior Machine Learning Engineer; MLOps

About Simpli Safe

Simpli Safe is a leading innovator in the home security industry, dedicated to making every home a safe home. With a mission to provide accessible and comprehensive security solutions, we design and build user-centric products that empower individuals and families to protect what matters most.

We believe in a collaborative and agile environment where learning and growth are continuous. Our teams are composed of talented individuals who are passionate about technology, security, and delivering exceptional customer experiences.

We're embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state‑of‑the‑art office on two core days, typically Tuesday, Wednesday, or Thursday – working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done.

Well, we’re growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure.

We are looking for an experienced MLOps Engineer to join our team as a Senior Machine Learning Engineer. In this role, you will drive the development and deployment of machine learning models, optimize ML workflows, and help ensure our infrastructure is scalable, reliable, and secure. If you have a passion for automation, cloud technology, and delivering high‑impact solutions, we’d love to hear from you.

• Lead the architecture, deployment, and optimization of scalable ML model serving systems for real‑time and batch use cases.
• Collaborate with data scientists, engineers, and stakeholders to operationalize ML models.
• Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases.
• Design, implement, and own comprehensive production monitoring for ML models/systems.
• Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads.
• Drive best practices in model versioning, observability, reproducibility, and deployment reliability.
• Serve in an on‑call rotation as a first responder for software owned by your team.

• 5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure.
• Deep hands‑on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks.
• Hands‑on experience with:
• CI/CD pipelines, Docker
• Kubernetes
• Infrastructure‑as‑code tools (e.g., Terraform, Cloud Formation).
• Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., Tensor Flow, PyTorch).
• Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring.
• LLM application development, including prompt engineering and evaluation.
• Strong communication skills for partnering with cross‑functional technical and non‑technical teams.

• Experience with Ray for inference, or pipeline orchestration
• Hands‑on experience with deploying large language models (LLMs) to production.
• Experience with frameworks such as vLLM is a plus.
• Experience with distributed systems and big data technologies (e.g., Spark, Hadoop).
• Experience with event‑driven or streaming architectures (e.g., Kafka, Kinesis).
• Knowledge of cloud security, IAM, and compliance best practices for ML workloads.

• Customer Obsessed – Building deep empathy for our customers, putting them at the core of our work, and developing strong, long‑term relationships with them.
• Aim High – Always challenging ourselves and others to raise the bar.
• No Ego – Maintaining a "no job too small" attitude, and an open, inclusive and humble style.
• One Team – Taking a highly collaborative approach to achieving success.
• Lift As We Climb – Investing in developing others and helping others around us succeed.
• Lean & Nimble – Working with agility and efficiency to experiment in an…